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--> --> -->Precipitation evolution during TC formation has recently begun to receive more attention in the literature. (Wang et al., 2016a) analyzed composites of precipitation and column water vapor retrieved from the SSM/I and SSMIS passive microwave instruments during TC formation. It was found that precipitation is weak and scattered in the radial direction prior to 48 hours before formation, followed by high column water vapor near the pouch center increasing prior to genesis, then precipitation increasing substantially and distributing more symmetrically, as a result of deep convection bursting in the pouch center. Moreover, latent heat releases of cloud microphysical processes associated with precipitation, such as water vapor condensation and deposition, are important for driving the transverse circulation and strengthening the low-level circulation in TC formation (Montgomery et al., 2006; Wang et al., 2010b). The intensification of the secondary circulation is attributed to the concentrated latent heating induced by the organized convection and the associated low-level inflow moisture convergences at large radii, fueling further precipitation in turn (Fritz and Wang, 2014). From the energy budget perspective, (Wang et al., 2016a) suggested that the latent heat released by moist convection accumulates and transforms into potential energy, and eventually converts to the horizontal kinetic energy of the near-surface circulation, indicating the spin-up of the TC vortex. (Raymond et al., 2011) and (Raymond, 2012) also found that increased stabilization of the atmosphere, as a result of latent heating in the middle troposphere and latent cooling in the lower troposphere, is conducive to the transition of the upward mass flux profile from top-heavy to bottom-heavy. As a result, the increasing vertical gradient of vertical mass flux induces convergence of mass and vorticity at a shallow layer in the lower troposphere, leading to the spin-up of a vortex near the surface.
During TC genesis, the water vapor content and cloud structures are closely related to dynamic and thermodynamic conditions of atmosphere. In this study, the 3D WRF-based precipitation equation (Huang et al., 2016) is for the first time applied in TC genesis, in which the contributions of moisture-related processes and hydrometeor-related processes to the precipitation during the formation of TC Durian (2001) are quantitatively diagnosed based on high-resolution simulation data (Wang et al., 2016b). The roles of cloud microphysical processes and their associated latent heating in TC formation will also be investigated. This study could give some hints on how moisture and cloud hydrometeors, as well as precipitation evolution, affect the establishment of the near-surface vortex in TC genesis.
The paper is organized as follows. Section 2 briefly describes the 3D WRF-based precipitation equation. Section 3 presents the rainfall processes, including water vapor-related processes and hydrometeor-related processes associated with the formation of TC Durian. Section 4 emphasizes the microphysical conversion processes and their related latent heat releases during TC formation in more detail, as well as their role in the TC vortex spin-up. A summary and conclusions are provided in section 5.
Equation (1) is derived based on the governing equations for water species in the WRF model (Skamarock et al., 2008): \begin{eqnarray} \dfrac{\partial(\rho_{\rm a}Q_{\rm v})}{\partial t}&\!=\!&{\rm ADV}_{Q_{\rm v}}\!+\!{\rm DIFF}_{Q_{\rm v}}\!+\!E_{\rm s}+\rho_{\rm a}S_{Q_{\rm v}}; \ \ (2)\\ \dfrac{\partial(\rho_{\rm a}Q_{\rm c})}{\partial t}&\!=\!&{\rm ADV}_{Q_{\rm c}}\!+\!{\rm DIFF}_{Q_{\rm c}}\!+\!\rho_{\rm a}S_{Q_{\rm c}}; \ \ (3)\\ \dfrac{\partial(\rho_{\rm a}Q_{\rm x})}{\partial t}&\!=\!&{\rm ADV}_{Q_{\rm x}}\!+\!{\rm DIFF}_{Q_{\rm x}}\!+\!{\rm SEDI}_{Q_{\rm x}}\!+\!\rho_{\rm a}S_{Q_{\rm x}},{\rm x}\!\in\! ({\rm r,i,s,g,h}) . \ \ (4) \end{eqnarray} Here, Qv, Qc, and Qx are the mixing ratios of water species (v: water vapor; c: cloud water; r: rain water; i: cloud ice; s: snow; g: graupel; h: hail); terms ADVQv=-?3$\cdot$(ρaQvV), ADVQc=-?3$\cdot$(ρaQcV), and ADVQx=-?3$\cdot$(ρaQxV) are 3D advection terms or 3D flux convergence/divergence terms; terms DIFFQ v, DIFFQ c and DIFFQx are diffusion terms; Es is the surface moisture flux; SEDIQx is the sedimentation term; ρa is the air density; V is the three-dimensional wind vector; and SQv, SQc and SQx are source/sink terms associated with cloud microphysical processes. A 3D WRF-based precipitation equation was derived from the above equations, Eqs. (2)-(4), by combination and vertical integrations (Huang et al., 2016):
Here, zt and zb are the top and surface of the model atmosphere, respectively. Note that QWVL, QCLL and QCIL are actually the negative values of vertically integrated ?(ρaQv)/? t, ?(ρaQx)/? t[ x( c,r)], and ?(ρaQx)/? t[ x( i,s,g,h)], respectively. The surface precipitation rate (PS) is associated with both water vapor-related processes (QWV) and hydrometeor-related processes (QCM). The two kinds of processes are not independent but interact intricately with each other, together determining the rain rate. QWV include four components: the water vapor local change rate (QWVL), 3D moisture flux convergence/divergence rate (QWVA), 3D water vapor diffusion rate (QWVD), and surface evaporation rate (QWVE). QCM include liquid-phase and ice-phase hydrometeor-related processes: the local change rate of liquid-phase hydrometeors (cloud water and rain water) (QCLL), 3D liquid-phase hydrometeor flux convergence/divergence rate (QCLA), 3D diffusion rate of liquid-phase hydrometeors (QCLD), local change rate of ice-phase hydrometeors (cloud ice, snow, graupel and hail) (QCIL), 3D ice-phase hydrometeor flux convergence/divergence rate (QCIA), and 3D diffusion rate of ice-phase hydrometeors (QCID) (Table 1). They are expressed as follows: \begin{eqnarray} Q_{\rm WV}&=&Q_{\rm WVL}+Q_{\rm WVA}+Q_{\rm WVD}+Q_{\rm WVE}; \ \ (6)\\ Q_{\rm CM}&=&Q_{\rm CLL}+Q_{\rm CLA}+Q_{\rm CLD}+Q_{\rm CIL}+Q_{\rm CIA}+Q_{\rm CID} . \ \ (7)\end{eqnarray} The meanings of each term and their sub-terms in Eqs. (1), (6) and (7) are presented in Table 1.
3.1. Model configuration and precipitation evolution
The formation process of TC Durian (2001) in the South China Sea (SCS) was successfully simulated by the WRF model with four nesting domains, the resolutions of which were 54, 18, 6, and 1.2 km, respectively (Wang et al., 2016b). The 54-km and 18-km domains integrated for 84 hours, starting at 0000 UTC 28 June and ending at 1200 UTC 1 July 2001, driven by NCEP reanalysis data on 2.5°× 2.5° grids. The 6-km and 1.2-km domains started at 1200 UTC 28 June, 12 hours later than the outer two domains, for the purpose of saving computer resources and allowing the environment to develop in the outer domains. The Goddard microphysics scheme (Tao et al., 1989) and Yonsei University boundary layer scheme (Hong et al., 2006) were used in each domain, while the Kain-Fritsch cumulus parameterization scheme (Kain, 2004) was only used in the outermost two domains. The simulated Durian generated near (16°N, 116.2°E) (about 80 km from the best track data) at about 0800 UTC 29 June 2001, which was just two hours later than observed.The 6-h accumulated precipitation amounts derived from passive microwave satellite measurements via the Climate Prediction Center morphing technique (CMORPH; Joyce et al., 2004) (Figs. 1a, c, e and g) and simulated by the WRF model (Figs. 1b, d, f and h) are shown in Fig. 1. From 1800 UTC 28 to 0000 UTC 29 June 2001, the satellite-estimated northwest-southeast-oriented rainband associated with a mesoscale convective system (MCS) before Durian's genesis (Fig. 1a) was reproduced fairly well by the model (Fig. 1b). The difference between the satellite-estimated and simulated precipitation intensities may be mainly due to the underestimation of TC rainfall intensities by the satellite (Sapiano and Arkin, 2009; Yu et al., 2009; Pan et al., 2011; Chen et al., 2015), as well as the relatively coarser horizontal resolution of the satellite estimation (8 km) than the simulation (1.2 km). From 0000 to 0600 UTC 29 June 2001, the satellite-estimated precipitation center near (14°N, 116°E) (Fig. 1c) gradually separated from the MCS rain belt and later developed into the TC-associated precipitation (Figs. 1e and g). Meanwhile, the simulated scattering precipitation (Fig. 1b) to the north of the MCS gradually developed and intensified with cyclonic distribution, and at the same time the rainband associated with the MCS was gradually narrowing and weakening (Figs. 1d, f and h). Overall, despite some differences between the satellite-estimated and the simulated precipitation, the WRF model basically reproduced the evolution characteristics of rainfall associated with the MCS, as well as the TC spin-up.
Figure1. Six-hour accumulated precipitation (units: mm) retrieved from (a, c, e, g) satellite measurements via the CMORPH technique with a horizontal resolution of 8 km, and (b, d, f, h) the model with a horizontal resolution of 1.2 km: (a, b) 1800 UTC 28 June to 0000 UTC 29 June; (c, d) 0000 UTC to 0600 UTC 29 June; (e, f) 0600 UTC to 1200 UTC 29 June; (g, h) 1200 UTC to 1800 UTC 29 June.The time series of the satellite-estimated and simulated rain rates averaged in a 240 km-radius circular domain are presented in Fig. 2. The centers of the circular domains were selected as the centers of a midlevel mesoscale convective vortex (MCV) before Durian's formation and the TC centers after its genesis, moving with time (Wang et al., 2016b). The midlevel MCV formed a favorable area for TC genesis, just like the pouch areas described in (Dunkerton et al., 2009) and (Wang et al., 2010b). The satellite-estimated rain rate was much smaller than the simulated one before 2300 UTC 28 June 2001, but after that the simulated rain rate followed the satellite-estimated one reasonably well. The difference in rain rates was due to the differences in rainfall distributions and intensities between the satellite estimation and simulation. With the formation of TC Durian (0200-1400 UTC 29 June 2001), both the satellite-estimated and simulated rain rates gradually decreased, and then increased as Durian began to intensify after 1400 UTC 29 June 2001.
Figure2. Time series of (a) area-averaged surface rain rate (PS, solid line), moisture-related processes (QWV, long dashed line), and cloud-related processes (QCM, short dashed line) (units: mm h-1), and (b) the ratios (units: %) of QWV (long dashed line) and QCM (short dashed line) to PS from 1400 UTC 28 June to 2000 UTC 29 June 2001 in a 240-km-radius domain.2
3.2. Surface rainfall processes during TC Durian's genesis
The time series of area-averaged (in the 240 km-radius circular domain) terms in the 3D WRF-based precipitation equation [Eqs. (1), (6) and (7), Table 1] from 1400 UTC 28 to 2000 UTC 29 June 2001 are shown in Fig. 3. QWV was the major contributor to the PS (Fig. 3a), accounting for more than 70% of it (Fig. 3b). Before Durian's genesis, the ratio of QWV to PS was relatively small (around 80%), and the ratio increased distinctly during and after Durian's formation (Fig. 3b). QCM accounted for around 20% of the PS before TC genesis, and the ratio of QCM to PS decreased quickly during genesis, followed by reactivation as Durian began to intensify (Fig. 3).
Figure3. Time series of area-averaged precipitation from CMORPH satellite data (dashed line) and from the model simulation (solid line) in a 240-km-radius area (units: mm h-1) from 1400 UTC 28 June to 2000 UTC 29 June 2001.According to Eq. (6), QWV consists of four parts: QWVL, QWVA, QWVE and QWVD (Fig. 4a). QWVA presented similar magnitude and evolution as QWV (Fig. 4a). Moisture flux convergence (QWVA>0) dominated the water vapor budget (QWV) over the ocean, with distinct "lower-tropospheric convergence superposed with upper-level divergence" structure (Fig. 5b) and upward vertical mass flux (Fig. 5a). Before Durian's genesis (1400 UTC 28 to 0200 UTC 29 June 2001), a mature MCS existed (Fig. 1b), with a thicker convergence level (Fig. 5b) and higher upward vertical mass flux center (Fig. 5a). Besides, a positive relative vorticity center existed in the mid-troposphere, with a maximum value located at around 4 km (Fig. 5c). (Zhang et al., 2008) and (Wang et al., 2016b) suggested that the midlevel cyclonic relative vorticity could be attributed to the development of a mid-level MCV on the north side of the MCS, which formed a favorable environment for Durian's genesis. The thicker lower-tropospheric convergence level (Fig. 5b) and higher upward vertical mass flux center (Fig. 5a) before Durian's genesis were mainly caused by the MCS. The MCS gradually moved out of the 240 km-radius circular domain during 2200 UTC 28 June to 0200 UTC 29 June. Thus, the upward vertical mass flux (Fig. 5a), the low-level convergence (Fig. 5b) and QWVA (Fig. 4a) slightly decreased. From 0200 to 0800 UTC 29 June 2001, convection gradually organized in the strengthening MCV (Wang et al., 2016b) (Fig. 1d), producing a vertical upward mass flux center at about z=5 km (Fig. 5a) and distinct lower-tropospheric convergence (Fig. 5b). Meanwhile, the positive relative vorticity center moved from around 4 km to ～1.5 km (Fig. 5c), suggesting gradual establishment of the lower-tropospheric TC vortex (Fig. 1d). After Durian's genesis at 0800 UTC 29 June 2001, with gradual intensification of the TC vortex, positive vorticity amplified (Fig. 5c). Meanwhile, the vertical upward mass flux (Fig. 5a), the low-level convergence (Fig. 5b) and QWVA (Fig. 4a) also intensified. Apart from the dominant role of QWVA in QWV (Fig. 4a), QWVE also made an indispensable positive contribution to QWV. Considering the surface evaporation outside the 240 km-radius circular domain, which could be further transported (QWVA) into the circular domain, the contribution of surface evaporation from the ocean to QWV should be bigger. QWVL was generally small during the analysis period (Fig. 4a), while just before Durian's genesis (From 0200 to 0800 UTC 29 June 2001) QWVL presented distinct negative values (Fig. 4a), which suggested the local atmospheric volume (in the 240 km-radius circular domain) was moistening due to sufficient water vapor supply.
Figure4. Time series of area-averaged (a) moisture-related processes [QWV (black solid line), consisting of QWVL (red slid line), QWVA (blue solid line), QWVD (greed solid line), and QWVE (pink solid line)], (b) surface rain rate (PS, black dash line) and liquid-phase cloud-related processes [QCL (black solid line), consisting of QCLL (red solid line), QCLA (blue solid line) and QCLD (green solid line)], and (c) surface rain rate (PS, black dash line) and ice-phase cloud-related processes [QCI (black solid line), consisting of QCIL (red solid line), QCIA (blue solid line) and QCID (green solid line)] from 1400 UTC 28 June to 2000 UTC 29 June 2001 in a 240-km-radius domain. The vertical dashed line represents the genesis time of the TC and the horizontal dashed line represents "0". Units: mm h-1.
Figure5. Time series of area-averaged (a) vertical mass flux (units: 10-2 kg m-2 s-1), (b) divergence (units: 10-5 s-1), and (c) vertical relative vorticity (units: 10-5 s-1) in a 240-km-radius domain.The rate of hydrometeor-related processes (QCM) includes two parts: rates of liquid-phase and ice-phase hydrometeor-related processes [Eq. (7)]. Liquid-phase hydrometeors consist of cloud water and rain water, while ice-phase hydrometeors consist of cloud ice, snow and graupel in this study. The rates of each term [Eq. (7) and Table 1] during the analysis period are presented in Figs. 4b and c. The 3D flux convergence/divergence rates (QCLA, QCIA) and the local change rates (QCLL, QCIL) of hydrometeors were the dominant terms in both liquid-phase and ice-phase hydrometeor-related rates (Figs. 4b and c). Before Durian's formation at 0800 UTC 29 June, QCLA and QCIA both made a positive contribution to QCM, especially QCIA. Positive QCLA and QCIA suggested that there were hydrometeors aggregating into the 240 km-radius circular volume. From 0400 to 1400 UTC 29 June, both QCLA and QCIA decreased to about zero, but with small positive QCLA and negative QCIA due to the vertical dynamical structure (Fig. 5b). This will be analyzed in detail later. After 1400 UTC 29 June, both positive QCLA and negative QCIA increased slightly due to the intensified "lower-tropospheric convergence superposed with upper-level divergence" dynamical structure (Fig. 5b) during Durian's intensification. The variations of local change rates of hydrometeors (QCLL, QCIL) were mainly caused by the 3D flux convergence/divergence rates of hydrometeors (QCLA, QCIA), the microphysical conversion rates, as well as the PS [Eqs. (3) and (4)]. Before 0000 UTC 29 June, both QCLL and QCIL were positive, suggesting a continuous decrease in hydrometeors in the MCS (Fig. 1) to feed the rainfall. From 0000 to 0800 UTC 29 June, with the decreasing PS (Fig. 3a), aggregation of hydrometeors by flux convergence (Figs. 4b, c), and cloud system spin-up (Fig. 1) due to microphysical processes, both QCLL and QCIL became negative, suggesting the development of TC-related cloud hydrometeors. After 0800 UTC 29 June, short-term small and positive QCLL and QCIL may have been mainly caused by consumption due to rainfall (Fig. 3a) under a relatively weak "lower-tropospheric convergence superposed with upper-level divergence" dynamical structure (Fig. 5b). Later, with the re-strengthening vertical "lower-tropospheric convergence superposed with upper-level divergence" dynamical structure (Fig. 5b), hydrometeors in the 240 km-radius circular volume increased distinctly again (negative QCLL and QCIL; Figs. 4b and c).
The 3D flux convergence/divergence term of hydrometeors [ ADVQ x=-?3$\cdot$(ρaQxV), x( c,r,i,s,g) in Eqs. (3) and (4)] can be divided into the horizontal part [-?h$\cdot$(ρaQxV), the vertical integration of which is denoted as QCXA_H] and the vertical part [-?v$\cdot$(ρaQxV), the vertical integration of which is denoted as QCXA_V]. During the analysis period of this study, QCXA_V turned out to be much smaller than QCXA_H (not shown), indicating that the horizontal advection of hydrometeors into or out of the 240 km-radius circular volume was more significant. Such a result is different from the conclusions in (Xu et al., 2017), stating that hydrometeor loss/convergence is related to the increased vertical advection of hydrometeors, while hydrometeor gain/divergence is associated with the decreased horizontal advection of hydrometeors. Liquid-phase hydrometeors (cloud water and rain water) were mainly distributed below z=6 km (Figs. 6a and b). Induced by the low-level horizontal convergence below z=9 km (Fig. 5b), the flux convergence of liquid-phase hydrometeors (QCLA_H>0) occurred (Fig. 7). Before 0200 UTC 29 June, QCLA_H generally increased. With the distinct decrease in rain water (Fig. 6b), as well as the apparent constriction of vertical convergence thickness and the decrease in upper-level divergence (Fig. 5b), QCLA_H (Fig. 7) and QCLA (Fig. 4b) markedly decreased. Later, with the intensification of Durian, as well as the simultaneous enhancement of lower-tropospheric convergence and upper-level divergence (Fig. 5b), QCLA_H (Fig. 7) and QCLA (Fig. 4b) increased again.
Figure6. Time-height cross sections of cloud hydrometeors: (a) cloud water (Qc), (b) rain water (Qr), (c) cloud ice (Qi), (d) snow (Qs) and (e) graupel (Qg), area-averaged in the 240-km-radius domain from 1400 UTC 28 June to 2000 UTC 29 June 2001. Units: 10-3 g g-1.
Figure7. Vertical profiles of area-averaged horizontal advection terms of liquid-phase hydrometeors (QCLA_H) and ice-phase hydrometeors (QCIA_H) in the 240-km-radius domain from 1400 UTC 28 June to 2000 UTC 29 June 2001. Units: 10-6 kg m-3 h-1.The ice-phase hydrometeors (cloud ice, snow and graupel) were mainly distributed above 4 km (Figs. 6c-e). Before 2000 UTC 28 June, negative QCIA_H appeared above 9 km (Fig. 7) due to distinct upper-level divergence (Fig. 5b) and deep distributions of ice-phase hydrometeors (Figs. 6c-e). From 1800 UTC 28 to 0200 UTC 29 June, considerable positive QCIA_H appeared between 4 km and 12 km (peaking between 6 km and 7 km), due to slightly enhanced lower-tropospheric convergence (Fig. 5b) and apparent distributions of snow and graupel (Figs. 6d and e). After 0200 UTC 29 June, with the distinct constriction of lower-tropospheric convergence thickness (Fig. 5b), the ice-phase hydrometeor convergence between 4 and 9 km at 0400 UTC 29 June converted to divergence above 4 km (Fig. 7). Meanwhile, due to the apparent decreases in ice-phase hydrometeors (Fig. 6), the magnitude of the above divergence above 4 km was relatively small (Fig. 7). Later, with the simultaneously enhancement of lower-tropospheric convergence and upper-level divergence (Fig. 5b) associated with the intensification of Durian, as well as the increases in ice-phase hydrometeors (Fig. 6), the magnitude of negative QCIA_H increased slightly (Fig. 7).
The aforementioned analyses suggest that the precipitation during Durian's formation period was directly determined by the distribution of water species (water vapor and hydrometeors) and the environmental dynamics. At the same time, water species usually interact with each other in terms of microphysical conversion processes, which could exert crucial influence on the environmental thermodynamics and dynamics through latent heating or cooling. In the following section, the role played by microphysical latent heat in Durian's formation will be addressed.
Figure8. Time series of the main vertically mass-integrated and area-averaged cloud microphysical conversion processes and the sum of all the conversion rates associated with (a) rain water, (b) cloud water, (c) ice, (d) snow and (e) graupel in the 240-km-radius domain from 1400 UTC 28 June to 2000 UTC 29 June 2001. Ern: evaporation of rain; Pgmlt: melting of graupel; Pracw: accretion of cloud water by rain water; Dgacw: accretion of cloud water by graupel; Cnd: condensation of water vapor; Psaci: the accretion of cloud ice by snow; Dep: deposition of water vapor; Wgacs: accretion of snow by graupel; Psmlt: melting of snow; Pracs: accretion of snow by rain water. Units: mm h-1.On the other hand, the microphysical conversion processes not only contributed directly to the variations of hydrometeors but also indirectly impacted the thermodynamic environment of the atmosphere through latent heating/ cooling (Fig. 9), and further exerted impact on the dynamical structure. The latent heating rate associated with condensation was the largest, mainly distributing below 9 km (Fig. 9). The narrow level of net cooling rate near the surface resulted from a very small condensation heating rate and distinct cooling rate by evaporation, which was mainly located beneath 6 km (Fig. 9). The latent heating rate associated with deposition processes, located from 6 km to 14 km, was the second largest heating rate (Fig. 9). This result echoes that in (Cecelski and Zhang, 2016)——that no tropical depression (TD)-scale disturbance occurs when removing the latent heat of fusion owing to depositional growth, emphasizing the effect of ice-phase microphysical processes in TC formation. The cooling rate by melting processes was the second largest cooling rate, located from 3 km to 6 km (Fig. 9). The latent heating/cooling rates associated with freezing and sublimation processes were relatively small. (Cecelski and Zhang, 2016) also found that removing homogeneous freezing has little impact on the development of the TD-scale disturbance. The magnitude of the net latent heating rate reduced (Figs. 9a-c) along with Durian's formation, and increased as Durian began to intensify (Figs. 9d and e), corresponding well with the variations of microphysical conversion rates (Fig. 8), dynamical structures (Figs. 5a and b) and rain rate (Fig. 3a). Before Durian's genesis (Figs. 9a and b), the maximum net latent heating rate was located at 8 km. Just before Durian's genesis (Fig. 9c), the height of the maximum net latent heating rate lowered distinctly to 6 km, mainly due to the more considerable decrease in the maximum deposition heating rate than the maximum condensation heating rate. Other heating/cooling rates, such as sublimation, evaporation and melting cooling rates, also played roles. The decrease and downward shift of the net latent heating peak mainly resulted from the deactivation of microphysical processes under the control of varied dynamical structure (Fig. 5). The changed vertical profile of net latent heating rate, on the contrary, could modify the thermal and dynamical structures of the atmosphere. Along with the downward shift of the net latent heating peak (Figs. 9 and 10) in this study, the "lower-tropospheric convergence superposed with upper-level divergence" dynamical structure (Fig. 5b) changed, accompanied by a more bottom-heavy vertical mass flux profile (Fig. 5a). Hence, mass and vorticity would be converged in a shallower layer (Fig. 5b), aiding the TC vortex spin-up in the lower troposphere (Raymond and Sessions, 2007; Raymond and López-Carrillo, 2011; Gjorgjievska and Raymond, 2014). While emphasizing the precipitation features from a microphysical perspective, we should not neglect the contribution of the precipitation processes to the dynamic and thermodynamic environment during TC formation. (Wang et al., 2018a) compared the vorticity amplification among a set of sensitivity simulations of TC Durian (2001) with different convective and stratiform precipitation intensities. Results showed that inhibited precipitation, especially the inhibited convective precipitation, led to a weaker diabatic heating rate and upward mass flux, further retarding the near-surface vorticity convergence and amplification.
Figure9. Vertical profiles of temporally averaged and area-averaged latent heating/cooling rate associated with the sum of all cloud microphysical processes (total), condensation (con), evaporation (evp), freezing (frz), melting (mlt), deposition (dep) and sublimation (sub) processes in the 240-km-radius domain: (a) 1400 UTC to 2000 UTC 28 June; (b) 2000 UTC 28 to 0200 UTC 29 June; (c) 0200 UTC to 0800 UTC 29 June; (d) 0800 UTC to 1400 UTC 29 June; (e) 1400 UTC to 2000 UTC 29 June; (f) 2000 UTC 29 to 0200 UTC 30 June. Units: 10-4 J g-1.
Figure10. Time-height cross section of area-averaged net latent heating (units: 10-4 J g-1) in the 240-km-radius domain from 1400 UTC 28 June to 2000 UTC 29 June 2001.The effects of cloud microphysical conversion processes among different water species on the dynamic environment through latent heating/cooling were further diagnosed. The net latent heating center associated with the microphysical conversion processes became lower as the TC generated, as a result of less sublimation and more lower-tropospheric condensation. The downward shift of the latent heating center induced a more bottom-heavy upward mass flux profile, which was conducive to constraint of the lower-tropospheric convergence in a shallower layer and further helped the near-surface vortex spin-dup.
It should be noted that the above results are based on the water budget calculation of a single TC case from a numerical simulation using the WRF model. Although the water budget analysis method in this study is similar with those in some previous studies (Braun, 2006; Yang et al., 2011; Huang et al., 2014; Xu et al., 2017), the magnitude of the budget terms may be sensitive to the choice of microphysics scheme, the weather system and model configurations. Besides, many studies show that utilizing different microphysics schemes would result in significant changes in intensity and inner-core structure of TCs, as well as the associated clouds, precipitation, specific microphysical conversion processes and latent heating profiles (Wang, 2002; McFarquhar et al., 2006; Zhu and Zhang, 2006; Jin et al., 2014; Bao et al., 2016; Cecelski and Zhang, 2016). While (McFarquhar et al., 2006) and (Cecelski and Zhang, 2016) emphasized the importance of ice-phase cloud parameterizations for TC simulations, we also find a nonnegligible role played by ice-phase hydrometeor processes in precipitation processes and in diabatic heating during TC formation. More studies about rainfall processes and the latent heating profiles associated with microphysical processes, especially the ice microphysics parameterization, during TC genesis are needed to generalize the results from this study.
